Line Bot - Smarter Than Your Average Cart
- This is not just another industrial robot—it’s a campus logistics revolution on wheels.
- Designed to move small loads like waste bags, supplies, or anything people are too lazy to carry.
- It glides across the campus, tackling uneven terrain with independent suspension like an off-road champion.
- No unnecessary AI here—just a PlayStation joystick and pure mechanical efficiency.
- Who needs fancy automation when you can have full manual control and actually enjoy driving it?
- Built to be rugged, reliable, and resistant to questionable student experiments.
- Designed for efficiency but guaranteed to make heads turn as it rolls by.
- Powered by engineering, controlled by common sense, and driven by necessity.
- It’s not just a robot—it’s a smarter, tougher, and way more entertaining alternative to walking.
Final Project Conceptual Sketch
Objectives
- To design and develop a cost-effective Unmanned Guided Vehicle (UGV) for educational use.
- To provide an interactive learning tool for students to understand robotics, automation, and navigation systems.
- To enable students to program and control UGV movements in real-time.
- To integrate sensors and artificial intelligence for enhanced learning.
Design Considerations
- Structure: To integrate sensors and artificial intelligence for enhanced learning.
- Locomotion System: Differential drive with DC motors or stepper motors for smooth and controlled movement.
- Control System: Microcontroller-based (Arduino, Raspberry Pi) with easy-to-use programming interfaces.
- Navigation and Sensing: LiDAR, ultrasonic, or infrared sensors for obstacle detection and avoidance.
- Power Supply: Rechargeable battery with optimized power management.
- Communication & Connectivity: Bluetooth or Wi-Fi for remote control and programming.
Key Components
- Microcontroller (Arduino/Raspberry Pi)
- Servo or Stepper Motors
- Motor Drivers
- Power Supply Unit
- Sensors (limit switches, force sensors)
- 3D-printed or metal frame
- Communication Modules (Bluetooth/Wi-Fi)
Software and Programming
- Programming languages: Python, C++, or Blockly (for beginner-friendly interface)
- Simulation software: ROS (Robot Operating System) or Gazebo for virtual testing
- Control methods: Manual control, pre-programmed movements, or AI-based automation navigation
Applications in Education
- Teaching robotics and automation concepts in schools and universities.
- Conducting experiments in inverse kinematics and motion planning.
- Demonstrating AI integration and machine learning for robotics.
- Assisting in STEM workshops and hands-on training programs.
Challenges and Future Scope
- Reducing cost while maintaining efficiency and precision.
- Enhancing real-time responsiveness with better control algorithms.
- Expanding compatibility with different programming languages and AI models.
- Exploring advanced applications such as human-robot collaboration.
Conclusion
An Unmanned Guided Vehicle (UGV) for educational purposes serves as a fundamental tool for hands-on learning in robotics and automation. By developing an accessible and functional model, students can gain practical experience in programming, engineering, and problem-solving. Future enhancements in AI integration and adaptability can further expand its applications in education and real-world automation.
Initial Model